new bulgarian experience in test ranges contamination … · 2019. 9. 4. · bulgarian experience...

BULGARIAN EXPERIENCE IN TEST RANGES CONTAMINATION RESEARCH

HRISTO P. HRISTOV1

HRISTO I. HRISTOV1

Abstract: On the base of NATO acknowledgedmethods for evaluation of

the environmental impact of using munitions on testing areas the

Defence Institute in Bulgaria have been performing the aim of the

Bulgarian project in AVT - monitoring of heavy metals and residual

munitions constituents accumulated in soil and water on army test range

impact areas.

This study was designed to develop and adapt accessible for Bulgarian

laboratories techniques for assessing the potential for environmental

contamination from energetic materials and heavy metals. Techniques

are being developed to define the influence of physical and chemical

properties, concentration, and distribution of energetics and residues of

energetics in soils and water to the current environment state.

The study has shown that impact areasare place with low level of

contamination where hot spots have been formed(Fig. 1). Analyses of

these residues define concentrations and spatial distributions of

munitions constituents under various firing activities for specific

munitions.

1 MINISTRY OF DEFENCE, Defence Institute, 34 Gen. Eduard Totleben Blvd, 1606 Sofia,

Bulgaria, Tel +359 2 92 21851 / Fax +359 2 92 21808 / email:[email protected]

mailto:[email protected]

HRISTO P. HRISTOV, HRISTO I. HRISTOV 2

39NIL

47NIL

41NIL

42TNT


3

There are following conclusion for the studied area:

- Multi-increment sampling strategies have been used for the

determination of the mean concentration of energetic materials

determination.

- A method for extraction and quantitative identification of energetics in

soil by HPLC with photo diode detection was developed, verified and

calibrated in accordance EPA Method 8330B, EPA Method 8000 and

EPA Method 3500, moreover the method was developed especially for

available laboratory techniques in Ministry of Defence and Ministry of

Interior in Bulagria.

- A Software and data bases are created in Defence Institute. The

Software’s role is to help estimation and visualization of Ranges Soil’s

pollution state and condition.

INTRODUCTION

In accordance with chemical laws every chemical reaction cannot be

accomplished to the end. The detonation burning of explosives in munitions is

not an exception to this rule and using devices equipped with explosive

materials is attended with emission of gases and solid dust contains heavy

metals and residual munitions constituents, which can accumulate in soils and

pollute shooting test ranges. Consideration of the obtained results from

pollution assessment and analysis will be base to develop measures to pollution

prevention and reduction in future.

In the other hand the readiness of the Armed Forces depends on and is

predicated on well-trained troops and continuous enhancements of munitions

arsenal. Sustained use of live-fire training ranges is especially critical to

Bulgarian missions abroad. That training activities potentially generate

environmental contamination in the form of residual munitions constituents.

The state of knowledge concerning the nature, extent, and fate of residual

munitions constituents is inadequate to ensure environmental stewardship on

testing and training ranges.

On the base of NATO acknowledgedmethods for evaluation of the

environmental impact of using munitions on testing areas the Defence Institute

in Bulgaria have been performing the aim of the Bulgarian project in AVT -

monitoring of heavy metals and residual munitions constituents accumulated in

soil and water on army test range impact areas.

This study was designed to develop and adapt accessible for Bulgarian

laboratories techniques for assessing the potential for environmental

contamination from energetic materials and heavy metals. Techniques are being

developed to define the influence of physical and chemical properties,


concentration, and distribution of energetics and residues of energetics in soils

and water to the current environment state.

SAMPLING STRATEGY

Energetic residues generally are distributed heterogeneously as particles on the

surface. Because such particulate residues serve as the major source of potential

off-site migration of these compounds, it can be important to estimate the mass

of energetic materials in areas where they are present. Establishing the mass of

energetic residues within a decision unit is a practical way of dealing with areas

that contain both particles and chunks of neat material. To achieve more reliable

estimates of the mean residue concentration, multi-increment sampling

strategies have been used for environmental investigations.

Sampling experiments were conducted in an active mortar and artillery impact

range (Impact area 4 and impact area 3 - Fig. 1) to determine the best sampling

strategy for collecting representative surface soil samples to estimate mean

concentrations of residues of high explosives. Samples were collected around

the fire point place to determine if there was a concentration gradient near the

place.

The heavy metals concentrations in surface soils have been determined in

accordance with STANAG 4590.

Fire point

Impact area 1

Impact area 2

Impact area 3

Impact area 4

Fig.1. Main Impact Areas for Pollution Study.

To characterize the site for surface contamination, the impact areas were

divided into subsampling areas and were gridded into 100 m square grids as

shown in Fig.2. Each grid cell is sampled by taking 100 incremental samples in

a systematic sub-grid with an approximate spacing of 5 m between replicate

samples.


5

100 m

10

0 m

1000 m

Unapproachable

Place

Fig.2. Sampling Areas Gridded into 100 m Square Grids.

SAMPLE HANDLING AND TREATMENT

Individual increments of approximately 20 grams are collected from the top 1-4

cm of the soil surface with soil sampler (Fig.3) and consolidated into a clean

polyethylene bag.

Fig.3. Used Soil Sampler.

The samples were stored in polyethylene bags and were sent to Special Section

for Counter Terrorism’s Laboratory and to Central Military Laboratory for

processing and analysis.

SAMPLE ANALYSIS

A method for extraction and quantitative identification of HMX, RDX, Tetryl,

TNT, 2,4-DNT, 2,6-DNT, PETN and NG in soil by HPLC with photo diode

detection was developed in accordance EPA Method 8330B, EPA Method 8000

and EPA Method 3500. The developed method was calibrated and validated.

The Limit of Quantification (LoQ) for the developed method is 0.025 µg/ml for

TNT, 2,4-DNT, 2,6-DNT and RDX in acetonitrile solution and 0.0375 mg/kg in

soil. For HMX, NG and PETN LoQ is 0.050 µg/ml and 0.1 µg/ml for Tetryl.

The Limit of Detection (LoD) for the developed method has been determined

0.0125 µg/ml in acetonitrile solution.

Dried, sieved and extracted samples were analyzed with HPLC for HMX, RDX,

Tetryl, TNT, 2,4-DNT, 2,6-DNT, PETN and NG.Samples for heavy metals


were analyzed with spectrophotometer DREL-2000 and DREL-2500 for copper,

nickel, cobalt and zinc.

ANALYSIS RESULT

In analyzed 48 multi-increment samples from impact area 4 was found only

TNT.In 19 samples (40%) the concentration of TNT was under the LoQ (Limit

of Quantification).In others 29 samples (60%) were measured concentrations

from 0.024 mg/kg to 0.813 mg/kg.The distribution of soil samples according

their type and results is shown in Fig.4.

Fig.4. Distribution of Soil Samples According Type and Results fromImpact Area 4.

The calculated mean concentration is 0.085 mg/kg and STD is 0.1807 mg/kg.

The Distribution and concentration map is shown in Fig.5.

Fig.5. TNT Concentrations Map of Impact Area 4 (Sample Number/Concentration).

Statistical data about the measured concentrations of energetic materials is

shown below in Fig.6.


7

Fig.6. Statistical Data for Measured Concentration of TNT (mg/kg) in Soil Samples

from Impact Area 4.

In 37 samples from impact area 3 or 74 % were not found any energetic

substances.In analyzed 50 multi-increment samples were found TNT, NG, 2,4-

DNT and 2,6-DNT.

In 7 samples (14 %) was found TNT. The concentration in six of them was

under the LoQ (Limit of Quantification). In only one sample the concentration

of TNT was above the LoQ or 0,0557 mg/kg.

NG was found in 4 samples or in 8 % from all. The measured concentrations

were from 0.0583 mg/kg to 0.111 mg/kg.

In six samples (12 %) was found DNT. Four of them (8 %) consist 2,6-DNT

and two (4%) consist 2,4-DNT. The measured concentrations were for 2,6-DNT

from 0.0849 to 1,038 mg/kg and for 2,4-DNT from 0.0345 to 0.044 mg/kg.

The distribution of soil samples according to their type and results is shown in

Fig.7.

Fig.7. Distribution of Soil Samples from Impact Area 3 According to Type and Results.


The concentration map is shown in Fig.8.

39NIL

47NIL

41NIL

42TNT


9

mean concentration is 0.033 mg/kg. The result for copper is shown in Fig.10 in

comparison with preventive and permissible concentration.

Fig.10. Concentrations of Cu (mg/kg) in Comparison with Preventive and

Permissible Concentrations.

Nickel was wound in fourteen from fifteen samples. The maximal measured

concentration is 3.4 mg/kg which is approximately 20 times below the

preventive and approximately 23 times below the permissible concentration.

Calculated mean concentration is 0.34 mg/kg. The result for nickel is shown in

Fig.11 in comparison with preventive and permissible concentration.

Fig.11. Concentrations of Ni (mg/kg) in Comparison with Preventive and



Cobalt was wound in every one samples. The maximal measured concentration

is 0.9 mg/kg which is approximately 38 times below the preventive

concentration. Calculated mean concentration is 0.35 mg/kg. The result for

cobalt is shown in Fig.12 in comparison with preventive concentration.

Fig.12. Concentrations of Co (mg/kg) in Comparison with Preventive Concentrations.

Zinc was wound in every one samples. The maximal measured concentration is

3.2 mg/kg which is 50 times below the preventive and approximately 68 times

below the permissible concentration. Calculated mean concentration is 1.28

mg/kg. The result for nickel is shown in Fig.13 in comparison with preventive

and permissible concentration.

Fig.13. Concentrations of Zn (mg/kg) in Comparison with Preventive and


SOFTWARE AND DATA BASES FOR POLLUTION MONITORING


11

In the early version of dataflow for pollution monitoring of army test ranges,

data was in table format in MS World document. To skip any manual operations

of data conversion, parsing and filling into database tables is proposed a format

for unifying incoming data (Fig. 14).

Fig.14. Incoming data structure

On Fig. 14 is presented a structure of unified data for pollution monitoring of

army test ranges in universal XML format. The XML document containsan

administrative data about protocol number, date of measurement series and

structured substantial data of measured pollutions. This approach makes

possible to run fully automated procedure to fillthe data into designed database.

The logical model of this database is shown on Fig. 15.


Fig. 15. Database structure

Description of the tables and his more significant fields are as follows:

Places – the name of current impact area;

Measurements – field ProtocolNo is a protocol number of the current

measurements series, field Date in a date of measurements;

PollutantType – field Name- a master type of pollutant, typically this is

energetic, or metals substances;

PollutantSubType – field Name- pollutant as average value of measurement

substance, or listed pollutants as energetic (TNT, NG, RDX, DNT), or metals

(Cu, Ni, Co, Zn). The fields MeasurePre and MeasureMax points to

precautionary and maximum permissible value of this pollutant subtype;

Dimensions –indication of the measured value. This typically is mg/kg, or pH;

Pollutant – This is the relational foreign keys (FK). Field No contains the

number of point of the measurement, Coord_X, Coord_Y are the geographical

coordinates of the measurement, Measure is a numerical value of this pollutant,

Note is reserved for additional information, if it exists.

This logical model of data base for pollution monitoring of army test ranges is

used to creating a physical data structures in Relational Database Management

System (RDBMS). The used electronically map consists of collection of several

georeffered raster files in TIFF file format. The chosen georeferencing system is

ESRI-style world files for raster datasets.A native plug-in system is usedto

linkthe user interface with the QuantumGIS (Fig. 16). The software’s main goal

is tointeract with database management system for the input/output operations,

and to drive appropriate classes methods of the QGIS application program

interface (API) to graphical visualization.


13

Fig. 16 User Graphical Interface.

CONCLUSION

The study has shown that impact areas are place with low level of

contamination where hot spots have been formed. Analyses of these residues

define concentrations and spatial distributions of munitions constituents under

various firing activities for specific munitions. The heavy metals concentrations

in surface soils have been determined in accordance with STANAG 4590. The

results for Copper, Nickel, Cobalt and Zinc are under the preventive levels in

accordance with the Bulgarian national laws. Low concentrations of metals are

probably attributable to low levels of firing intensity and frequent debris

removal and tilling of the soil.

There are following conclusion for the studied area:

- Multi-increment sampling strategies have been used for the

determination of the mean concentration of energetic materials determination.

- A method for extraction and quantitative identification of energetics in

soil by HPLC with photo diode detection was developed, verified and calibrated

in accordance EPA Method 8330B, EPA Method 8000 and EPA Method 3500,

moreover the method was developed especially for available laboratory

techniques in Ministry of Defence and Ministry of Interior in Bulagria.

- A Software and data bases are created. The Software’s role is to help

estimation and visualization of Ranges Soil’s pollution state and condition.


REFERNCES

1. A Free and Open Source Geographic Information System,

http://www.qgis.org/en/site/.

2. Developing GIS data for the Web, Viewing TIFF

Images,http://gis.pima.gov/webdev/tiff.cfm.

3. PyQt4, http://www.riverbankcomputing.co.uk/software/pyqt.

4. Python Programming Language – Official Website,

http://www.python.org/.

5. Open Source Geospatial Foundation , http://www.osgeo.org/, acessed

oct. 2013.

6. SQLite, http://www.sqlite.org, acessed oct. 2013.

7. SQLite Studio, http://sqlitestudio.pl/, acessed oct. 2013.

8. World files for raster datasets,

http://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?pid=3034&topicname=

World_files_for_raster_datasets, acessed oct. 2013.

9. EPA Method 8330B, Revision 2, October 2006.

10. EPA Method 8000B, Revision 3, March 2003.

11. EPA Method 3500C, Revision 3, February 2007.

12. Huber L., Good Laboratory and Current Good manufacturing Practice.

Agilent Technologies Deutschland GmbH.

13. Jenkins T.F., Thorne P.G., McCormick E.F., Myres K.F., Preservation

of Water Samples Containing Nitroaromatics and Nitramines. Special Report

95-16 US Army Corps of Engineers Cold Regions Research & Engineering

laboratory.
http://gis.pima.gov/webdev/

new bulgarian experience in test ranges contamination … · 2019. 9. 4. · bulgarian experience...

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